How to use as_complex method in autotest

Best Python code snippet using autotest_python

curvelet.py

Source:curvelet.py

1import numpy as np2# -----------------------------------------------------------------------------3#                             FUNCTION API4# -----------------------------------------------------------------------------5def curvelet_transform(x, num_bands, num_angles = 8, all_curvelets = True, as_complex = False):6    ndims = len(x.shape)7    # This file requires Curvelab and the PyCurveLab packages be installed on your system.8    try:9        import pyct10    except ImportError:11        raise NotImplementedError("Use of curvelets requires installation of CurveLab and the PyCurveLab package.\nSee: http://curvelet.org/  and  https://www.slim.eos.ubc.ca/SoftwareLicensed/")12    if ndims == 2:13        ct = pyct.fdct2( n = x.shape,14                         nbs = num_bands,   # Number of bands15                         nba = num_angles,  # Number of discrete angles16                         ac = all_curvelets,# Return curvelets at the finest detail level17                         vec = False,       # Return results as nested python vectors18                         cpx = as_complex)  # Disable complex-valued curvelets19    elif ndims == 3:20        ct = pyct.fdct3( n = x.shape,21                         nbs = num_bands,   # Number of bands22                         nba = num_angles,  # Number of discrete angles23                         ac = all_curvelets,# Return curvelets at the finest detail level24                         vec = False,       # Return results as nested python vectors25                         cpx = as_complex)  # Disable complex-valued curvelets26    else:27        raise NotImplementedError("%dD Curvelets are not supported." % (ndims))28    result = ct.fwd(x)29    del ct30    return result31def inverse_curvelet_transform(coefs, x_shape, num_bands, num_angles, all_curvelets, as_complex):32    # This file requires Curvelab and the PyCurveLab packages be installed on your system.33    try:34        import pyct35    except ImportError:36        raise NotImplementedError("Use of curvelets requires installation of CurveLab and the PyCurveLab package.\nSee: http://curvelet.org/  and  https://www.slim.eos.ubc.ca/SoftwareLicensed/")37    if len(x_shape) == 2:38        ct = pyct.fdct2( n = x_shape,39                          nbs = num_bands,     # Number of bands40                          nba = num_angles,41                          ac = all_curvelets,42                          vec = False,43                          cpx = as_complex)44    else:45        ct = pyct.fdct3( n = x_shape,46                          nbs = num_bands,     # Number of bands47                          nba = num_angles,48                          ac = all_curvelets,49                          vec = False,50                          cpx = as_complex)51    result = ct.inv(coefs)52    del ct53    return result54# -----------------------------------------------------------------------------55#                         OBJECT-ORIENTED API56# -----------------------------------------------------------------------------57class CurveletTransform(object):58    def __init__(self, x_shape, num_bands = None, num_angles = 8, all_curvelets = True, as_complex = False):59        if num_bands == None:60            self._num_bands = int(np.ceil(np.log2(np.min(x_shape)) - 3))61        else:62            self._num_bands = num_bands63        self.x_shape = x_shape64        self.num_angles = num_angles65        self.all_curvelets = all_curvelets66        self.as_complex = as_complex67        self.example_coefs = self.fwd(np.zeros(x_shape))68    # ------------- Forward and inverse transforms ------------------69    def fwd(self, data, num_bands = None):70        '''71        Curvelets must have the num_bands initialized in the72        constructor, but for uniformity with the API for forward73        transforms, we allow the user to supply a num_bands74        argument.  If the supplied num_bands does not match the75        num_bands used in the constructor, an error is generated.76        '''77        if num_bands != None:78            assert self._num_bands == num_bands79        # Check argument80        assert data.shape == self.x_shape81        ndims = len(self.x_shape)82        if ndims == 1:83            raise NotImplementedError("1D curvelet transform not yet implemented.")84        elif ndims == 2:85            return curvelet_transform(data, self._num_bands, self.num_angles, self.all_curvelets, self.as_complex)86        elif ndims == 3:87            return curvelet_transform(data, self._num_bands, self.num_angles, self.all_curvelets, self.as_complex)88        else:89            raise NotImplementedError("Curveletes not supported for %dD data." % (len(data.shape)))90    def inv(self, coefs):91        ndims = len(self.x_shape)92        if ndims == 1:93            raise NotImplementedError("1D Inverse curvelet transform not yet implemented.")94        elif ndims == 2:95            return inverse_curvelet_transform(coefs, self.x_shape, self._num_bands, self.num_angles,96                                              self.all_curvelets, self.as_complex)97        elif ndims == 3:98            return inverse_curvelet_transform(coefs, self.x_shape, self._num_bands, self.num_angles,99                                              self.all_curvelets, self.as_complex)100        else:101            raise NotImplementedError("Curvelets not supported for %dD data." % (len(data.shape)))102    # --------------------- Utility methods -------------------------103    def num_bands(self, coefs):104        return self._num_bands105    def num_coefficients(self):106        total = 0107        for band in self.example_coefs:108            total += sum([ np.prod(angle.shape) for angle in band ] )109        return total110    def num_nonzero_coefficients(self, coefs):111        total = 0112        for band in coefs:113            total += sum([ angle.nonzero()[0].shape[0] for angle in band ] )114        return total115    def coefs_to_vec(self, coefs):116        return np.hstack([np.hstack([ angle.ravel(order = 'c') for angle in band ]) for band in coefs])117    def vec_to_coefs(self, coef_vec):118        base_idx = 0119        coefs = []120        for band in self.example_coefs:121            angle_list = []122            for angle in band:123                angle_size = np.prod(angle.shape)124                angle_list.append(np.reshape(coef_vec[base_idx:base_idx+angle_size], angle.shape, order = 'c'))125                base_idx += angle_size126            coefs.append(angle_list)127        return coefs128    def update(self, coefs, update, alpha):129        '''130        Adds the update (multiplied by alpha) to each set of131        coefficients.132        '''133        delta_sqrsum = 0.0134        for band in xrange(len(coefs)):135            for angle in xrange(len(coefs[band])):136                delta = alpha * update[band][angle]137                coefs[band][angle] += delta138                delta_sqrsum += np.square(delta).sum()139        update_norm = np.sqrt(delta_sqrsum)140        return (coefs, update_norm)141    def mean(self, coefs):142        '''143        Compute the average over all wavelet coefficients.144        '''145        accum = []146        for coef in coefs:147            accum.append(np.hstack( [ block.ravel() for block in coef ] ))148        return np.hstack(accum).mean()149    # ------------------ Thresholding methods -----------------------150    def _estimate_noise(self):151        '''152        Helper function for the thresholding function below.153        Adapted from the fdct_osfft_demo_denoise.m file in CurveLab.154        '''155        E_coefs = self.fwd(np.random.randn(*self.x_shape))156        E_thresholds = []157        for band in xrange(len(E_coefs)):158            angle_thresholds = []159            for angle in xrange(len(E_coefs[band])):160                A = E_coefs[band][angle]161                angle_thresholds.append( np.median(np.abs(A - np.median(A)))/0.6745 )162            E_thresholds.append(angle_thresholds)163        return E_thresholds164    def threshold_by_band(self, coefs, threshold_func, skip_bands = [], within_axis = None, scaling_factor = None):165        '''166        Threshold each band individually.  The threshold_func() should167        take an array of coefficients (which may be 1d or 2d or 3d),168        and return a tuple: (band_center, band_threshold)169        For the sake of speed and memory efficiency, updates to the coefficients170        are performed in-place.171        '''172        # Skip the lowest frequency band173        for b in xrange(1, len(coefs)):174            num_removed = 0175            num_total = 0176            # Skip band?177            if b in skip_bands:178                continue179            # print num_total - num_removed, num_total180            # Compute the center and threshold.181            tmp = np.hstack( [ angle.ravel() for angle in coefs[b] ] )182            (band_center, band_threshold) = threshold_func(tmp, b, None)183            # print '\t\t****', b, band_center, band_threshold184            #if scaling_factor != None:185            #    band_threshold /= scaling_factor186            for a in xrange(len(coefs[b])):187                # Soft threshold the coefficients188                idxs = np.where( coefs[b][a] > band_threshold )189                coefs[b][a][idxs] -= band_threshold190                idxs = np.where( np.abs(coefs[b][a]) <= band_threshold )191                coefs[b][a][idxs] = 0.0192                idxs = np.where( coefs[b][a] < -band_threshold )193                coefs[b][a][idxs] += band_threshold194                #idxs = np.where( np.abs( coefs[b][a] - band_center ) < band_threshold )#  * scaling_factor[b][a] / max_scale )195                #num_removed += idxs[0].shape[0]196                #num_total += np.prod(coefs[b][a].shape)197                #coefs[b][a][idxs] = 0.0198            #print 'Retained %0.2f -- ( %g / %g )' % (100.0*(num_total - num_removed)/float(num_total),199            #                                         num_total - num_removed, num_total)...

test_api.py

Source:test_api.py

1#!/usr/bin/env python2# -*- coding: utf-8 -*-3#4# parselglossy -- Generic input parsing library, speaking in tongues5# Copyright (C) 2020 Roberto Di Remigio, Radovan Bast, and contributors.6#7# This file is part of parselglossy.8#9# Permission is hereby granted, free of charge, to any person obtaining a copy10# of this software and associated documentation files (the "Software"), to deal11# in the Software without restriction, including without limitation the rights12# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell13# copies of the Software, and to permit persons to whom the Software is14# furnished to do so, subject to the following conditions:15#16# The above copyright notice and this permission notice shall be included in17# all copies or substantial portions of the Software.18#19# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR20# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,21# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE22# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER23# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,24# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE25# SOFTWARE.26#27# For information on the complete list of contributors to the28# parselglossy library, see: <http://parselglossy.readthedocs.io/>29#30"""Tests for `parselglossy` package."""31import json32from pathlib import Path33from shutil import rmtree34import pytest35from parselglossy import api36from parselglossy.utils import as_complex37@pytest.mark.parametrize(38    "args,out,reference",39    [40        (("tests/api/standard.inp",), None, "tests/ref/standard_ir.json"),41        (42            ("tests/api/scf.inp", "standard", "scf_ir.json"),43            "scf_ir.json",44            "tests/ref/scf_ir.json",45        ),46        (47            ("tests/api/getkw.inp", "getkw", "lex_ir.json"),48            "lex_ir.json",49            "tests/ref/getkw_ir.json",50        ),51    ],52    ids=["lex-default", "lex-standard-w-outfile", "lex-getkw-w-outfile"],53)54def test_api_lex(args, out, reference):55    ir = api.lex(*args)56    # Check intermediate representation matches with reference57    ref_json = Path(reference).resolve()58    if out is None:59        with ref_json.open("r") as f:60            assert ir == json.loads(f.read(), object_hook=as_complex)61    else:62        dumped = Path(out).resolve()63        with ref_json.open("r") as ref, dumped.open("r") as o:64            assert json.loads(o.read(), object_hook=as_complex) == json.loads(65                ref.read(), object_hook=as_complex66            )67        # Clean up JSON file68        dumped.unlink()69@pytest.mark.parametrize(70    "args,out,reference",71    [72        (73            ("tests/ref/scf_ir.json", "tests/validation/overall/template.yml"),74            None,75            "tests/ref/scf_fr.json",76        ),77        (78            (79                "tests/ref/scf_ir.json",80                "tests/validation/overall/template.yml",81                "scf_fr.json",82            ),83            "scf_fr.json",84            "tests/ref/scf_fr.json",85        ),86    ],87    ids=["validate-default", "validate-w-outfile"],88)89def test_api_validate(args, out, reference):90    fr = api.validate(*args)91    # Check final representation matches with reference92    ref_json = Path(reference).resolve()93    if out is None:94        with ref_json.open("r") as f:95            assert fr == json.loads(f.read(), object_hook=as_complex)96    else:97        dumped = Path(out).resolve()98        with ref_json.open("r") as ref, dumped.open("r") as o:99            assert json.loads(o.read(), object_hook=as_complex) == json.loads(100                ref.read(), object_hook=as_complex101            )102        # Clean up JSON file103        dumped.unlink()104@pytest.mark.parametrize(105    "args,out,reference",106    [107        (108            ("tests/api/scf.inp", "tests/validation/overall/template.yml"),109            None,110            "tests/ref/scf_fr.json",111        ),112        (113            (114                "tests/api/scf.inp",115                "tests/validation/overall/template.yml",116                "scf_fr.json",117            ),118            "scf_fr.json",119            "tests/ref/scf_fr.json",120        ),121        (122            (123                "tests/api/scf.inp",124                "tests/validation/overall/template.yml",125                None,126                "standard",127                True,128            ),129            None,130            "tests/ref/scf_fr.json",131        ),132    ],133    ids=["parse-default", "parse-w-outfile", "parse-w-dumpir"],134)135def test_api_parse(args, out, reference):136    fr = api.parse(*args)137    # Check final representation matches with reference138    ref_json = Path(reference).resolve()139    if out is None:140        with ref_json.open("r") as f:141            assert fr == json.loads(f.read(), object_hook=as_complex)142    else:143        dumped = Path(out).resolve()144        with ref_json.open("r") as ref, dumped.open("r") as o:145            assert json.loads(o.read(), object_hook=as_complex) == json.loads(146                ref.read(), object_hook=as_complex147            )148        # Clean up JSON file149        dumped.unlink()150@pytest.mark.parametrize(151    "args,out,reference",152    [153        (("tests/api/docs_template.yml",), None, "tests/ref/input.rst"),154        (155            ("tests/api/docs_template.yml", "input.rst"),156            "input.rst",157            "tests/ref/input.rst",158        ),159        (160            (161                "tests/api/docs_template.yml",162                "input.rst",163                "Dwigt Rortugal's guide to input parameters",164            ),165            "input.rst",166            "tests/ref/dwigt.rst",167        ),168    ],169    ids=["document-default", "document-w-outfile", "document-w-header"],170)171def test_api_document(args, out, reference):172    docs = api.document(*args)173    # Check final representation matches with reference174    ref_rst = Path(reference).resolve()175    if out is None:176        with ref_rst.open("r") as ref:177            assert docs == ref.read()178    else:179        dumped = Path(out).resolve()180        with ref_rst.open("r") as ref, dumped.open("r") as o:181            assert o.read() == ref.read()182        # Clean up .rst file183        dumped.unlink()184@pytest.mark.parametrize(185    "args,inp,references",186    [187        (188            {189                "template": "tests/validation/overall/template.yml",190                "docfile": "foo.rst",191                "grammar": "standard",192            },193            "tests/api/scf.inp",194            ("tests/ref/scf_fr.json", "tests/ref/generated_input.rst"),195        ),196        (197            {198                "template": "tests/validation/overall/template.yml",199                "docfile": "babar.rst",200                "grammar": [201                    Path(__file__).parents[1].absolute()202                    / f"parselglossy/grammars/{x}.py"203                    for x in ["atoms", "getkw"]204                ],205                "tokenize": "from . import getkw; lexer = getkw.grammar(has_complex=True); ir = lexer.parseString(in_str).asDict()",206            },207            "tests/api/scf.inp",208            ("tests/ref/scf_fr.json", "tests/ref/generated_input.rst"),209        ),210    ],211    ids=["generate-default", "generated-custom-grammar"],212)213def test_api_generate(args, inp, references):214    # generate parser215    parser_dir = api.generate(**args)216    # use generated parser to parse inp217    from input_parser import api as generated_api218    fr = generated_api.parse(inp)219    # Check final representation matches with reference220    ref_json = Path(references[0]).resolve()221    with ref_json.open("r") as ref:222        assert fr == json.loads(ref.read(), object_hook=as_complex)223    # Check generated documentation agrees with reference224    ref_rst = Path(references[1]).resolve()225    dumped = parser_dir / f"docs/{args['docfile']}"226    with ref_rst.open("r") as ref, dumped.open("r") as o:227        assert o.read() == ref.read()228    # clean up generated parser...

conversions.py

Source:conversions.py

1def int_to_str(value, width):2    """3    Outputs a string of the binary of the value with4    LSB to the left.5    """6    s = bin(value)[2:]7    assert len(s) <= width8    s = '0' * (width - len(s)) + s9    return s10def signed_to_slv(value, width):11    """12    Takes a value between -1 to 1 inclusive and maps it13    into `width` bits.14    >>> bin(signed_to_slv(1, 8))15    '0b1000000'16    >>> bin(signed_to_slv(-1, 8))17    '0b11000000'18    """19    assert abs(value) <= 120    max_mag = pow(2, width-2)21    scaled = round(value * max_mag)22    if scaled < 0:23        scaled = pow(2, width) + scaled24    assert scaled < pow(2, width)25    assert isinstance(scaled, int)26    return scaled27def slv_to_signed(value, width):28    max_mag = pow(2, width-2)29    if value >= pow(2, width-1):30        value = value - pow(2, width)31    scaled = value / max_mag32    assert scaled <= 133    return scaled34def complex_to_slv(value, width):35    """36    Maps a complex number, `value`, (with mag <= 1) to an integer with37    bit width of width `width`.38    >>> bin(complex_to_slv(1+0j, 12))39    '0b10000000000'40    >>> bin(complex_to_slv(0.5-0.5j, 12))41    '0b1000111000'42    """43    assert width % 2 == 044    assert abs(value) <= 145    mapped_real = signed_to_slv(value.real, width//2)46    mapped_imag = signed_to_slv(value.imag, width//2)47    mapped = mapped_imag + mapped_real * pow(2, width//2)48    return mapped49def complex_from_slv(value, width):50    """51    Maps an integer (with bit-width `width`)52    to a complex number.53    """54    assert value < pow(2, width)55    assert width % 2 == 056    real_part = value >> width//257    imag_part = value % pow(2, width//2)58    imag_float = slv_to_signed(imag_part, width//2)59    real_float = slv_to_signed(real_part, width//2)60    as_complex = real_float + imag_float * (0+1j)61    return as_complex62def list_of_complex_to_slv(values, width):63    slv = 064    f = 165    for value in values:66        slv += complex_to_slv(value, width) * f67        f = f << width68    return slv69def list_of_complex_from_slv(value, width, size):70    assert value < pow(2, width*size)71    bits = ''.join(reversed(bin(value)[2:]))72    assert len(bits) <= width * size73    bits += '0' * (width*size - len(bits))74    lumps = [bits[index*width: (index+1)*width]75             for index in range(size)]76    complexes = []77    for lump in lumps:78        as_int = int(''.join(reversed(lump)), 2)79        as_complex = complex_from_slv(as_int, width)80        complexes.append(as_complex)81    return complexes82def list_of_uints_to_slv(values, width):83    slv = 084    f = 185    step = pow(2, width)86    for value in values:87        slv += value * f88        f *= step89    return slv90def list_of_uints_from_slv(slv, width, size):91    step = pow(2, width)92    values = []93    for i in range(size):94        values.append(slv % step)95        slv = slv >> width96    assert slv == 097    return values98if __name__ == '__main__':99    import doctest...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.